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[PyTorch] Debug CUDA graph support with operation-based API #1117

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Description

This PR debugs CUDA graph support with the operation-based API (see #707). The CUDA graph logic is similar to the module-based API.

Type of change

  • Documentation change (change only to the documentation, either a fix or a new content)
  • Bug fix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds functionality)
  • Breaking change (fix or feature that would cause existing functionality to not work as expected)
  • Infra/Build change
  • Code refractor

Changes

  • Debug CUDA graph support with operation-based API
  • Refactor CUDA graph tests

Checklist:

  • I have read and followed the contributing guidelines
  • The functionality is complete
  • I have commented my code, particularly in hard-to-understand areas
  • I have made corresponding changes to the documentation
  • My changes generate no new warnings
  • I have added tests that prove my fix is effective or that my feature works
  • New and existing unit tests pass locally with my changes

@timmoon10 timmoon10 added the bug Something isn't working label Aug 16, 2024
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/te-ci pytorch

if fp8_recipe is None:
fp8_recipe = FP8GlobalStateManager.get_fp8_recipe()
if fp8_recipe is None:
fp8_recipe = get_default_fp8_recipe()
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Hmmmm, this second if looks like logic that should be inside get_fp8_recipe in the FP8GlobalStateManager.

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Also, since this is an internal function, couldn't we just always ask for a valid recipe here and just deal with getting it int the caller?

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This case shouldn't happen in any of our current use-cases (FP8GlobalStateManager.get_fp8_recipe() is set within fp8_autocast, fp8_recipe is provided within make_graphed_callables), but it seems delicate to rely on that assumption.

if curr_len == amax_history_len:
continue

# Reallocate amax history
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Could this be its own function?

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I've tried to keep this logic similar to how it's handled in the modules:

def adjust_amax_history_length(self, length: int, fwd: Optional[bool] = None) -> None:

I think it would be nice to consolidate this logic in fp8.py and reuse it for both modules and operations, but that's probably best done in a pure refactor PR.

@@ -260,6 +275,21 @@ def _maybe_update_fp8_meta(cls, fp8_meta: Optional[dict[str, Any]]) -> None:
pad=(0, 0, 0, amax_history_len - curr_len),
)

# Update global buffers for amax reductions
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@ptrendx ptrendx Sep 18, 2024

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This does not look like graph specific thing - was the lack of this in the previous code a bug?

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Yep, if the amax history length changes then I don't expect amax reductions to be handled correctly.

Return default recipe from FP8GlobalStateManager.get_fp8_recipe if needed. Expand error message when failing to load FP8 state after capturing CUDA graph.

Signed-off-by: Tim Moon <[email protected]>
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/te-ci pytorch

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2 participants